NCA-GENM Exam Dumps | You are building a multimodal generative A1 model that creates realistic indoor scenes by combining textual

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Question 55/192

You are building a multimodal generative A1 model that creates realistic indoor scenes by combining textual descriptions, floor plans (geospatial data), and object libraries. The goal is to generate high-quality 3D models of the scenes. However, the model often produces scenes with physically implausible object arrangements (e.g., objects floating in the air, overlapping furniture). How can you MOST effectively integrate physical constraints into the generation process to ensure more realistic scene compositions?

A. Increase the size of the training dataset with more examples of realistic indoor scenes.

B. Use a physics engine (e.g., NVIDIA PhysX) as a post-processing step to simulate the generated scene and correct any physically implausible object placements.

C. Implement a rule-based system that enforces basic physical constraints (e.g., objects must be supported by a surface, no object interpenetration) during the generation process.

D. Train a separate discriminator network that evaluates the physical plausibility of generated scenes and penalizes implausible configurations during training.

E. Force the model to generate only scenes that exist within the training set.

Correct Answer: B,C,D

Using a physics engine for post-processing (B) directly simulates physical interactions. Implementing a rule-based system (C) enforces basic constraints. Training a discriminator (D) adds a learning component for physical plausibility. Increasing the dataset size (A) might help but doesn't guarantee physical plausibility. Limiting generation to the training set (E) restricts creativity and generalization.

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